Why "Simplicity Sells"?

David Pogue, is the New York Times Columnist, often seen writing on technology, software, and new tools in the markets. Below is link to his presentation at TED series in 2006 on "Why Simplicity Sells". This presentation is more on the emerging technologies (some might find it more focused on PC and Mac) and simple modifications to the existing or new tools, can be more ergonomic.

One viewer commented on Daivd Pogue's presentation saying - ".. answering to the question 'What is essential?' is the same thinking about what people need. For the majority of users, that would be simplicity... we want software that allows us to do things in a minimum of steps and find things quickly. In that sense, yes, simplicity sells. A lot."

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The topic of our interest is the air pollution and management. This has never been a "simpler" task to crack. The air pollution modeling is the key step to better understand the local pollution sources, their emission strengths, and the potential to control the emissions for better ambient air quality and human health. I am not restricting this discussion to one pollutant, but in general the information and modeling of any of the pollutants (PM, SO2, NOx, CO, VOCs, or any of the GHGs) and their detrimental affects on human health is critical to sound and comprehensive pollution management plan for any city.

In order to make informed choices amongst the bewildering array of options, the city managers need to be able to analyze these options from an environmental, economic, social, and political economy viewpoint. All this requires flexible analysis frameworks to evaluate options as they emerge, which, in turn, need substantial quantities of relevant information on various aspects of air quality and characteristics of management options.

A number of tools (with varying degree of complexities) have been developed to analyze air pollution and benefits of management options. There are many institutions, all over the world, that have developed many useful models to simulate various parts of the air pollution modeling cycle. Of course, it would be excellent for all cities to develop a detailed knowledge base and have a working version of all the key appropriate models. However, there are a number of problems in the developing world. These include problems with:

• All Existing models are usually very data hungry, “super-specialized”, expensive, and inflexible to the context of developing countries (a summary of existing models is presented in this article)
  
• Environmental agencies in the developing cities are often young, with inadequate skills, interaction, and capacity (for example, most agencies function as a regulator instead of decision maker, which consumes most of the man power for compliance analysis instead of knowledge base development)
  
• Institutional problems are very common in the developing world (very initial public, bureaucratic, and political interest in environment and with competing demands for scarce financial resources; Decision-making is often ad-hoc and crisis-driven and there is often little time to develop a suite of high-end models for a bewildering array of options)
• Often detailed studies undertaken on a few parameters without a feel for how important these parameters are in the larger picture
• Updated relevant database that is accessible and of the required quality and consistency

Without undermining the importance of the existing models and the knowledge they share from the applications around the world, there is a need to develop simple and interactive tools for air quality management. The simplicity of a fundamental equation in developing the emissions inventory and evaluating their impact on the ambient air and human health, is still the basis for many of the cities in the developing world. Key is to establish a simple baseline to compare the future scenario or what can be done to improve the existing. Once a baseline is established, it will be a lot easier to complicate and further conduct detailed analysis on each of the parameters or under each of the emission sectors.

The SIM-air analytical tool "Simple Interactive Model for Better Air Quality" would aim to use the best available information and educated guesses to arrive at approximate “first-cut" estimates of key parameters (e.g. emissions from various sources based on logical criteria) and simulate the essence of interactions among emissions, dispersion, impacts and management options in an economic context.

Until a better understanding is established between "What is needed" and "What is available" to conduct air pollution analysis, yes, "Simplicity Sells". I think, most of the groups are still battling with "what is needed", instead of utilizing "what is available" to make that "first-cut".